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dc.contributor.advisorde Weck, Olivier L.
dc.contributor.authorTrujillo, Alejandro Elio
dc.date.accessioned2022-02-07T15:09:27Z
dc.date.available2022-02-07T15:09:27Z
dc.date.issued2021-09
dc.date.submitted2021-09-16T17:14:15.784Z
dc.identifier.urihttps://hdl.handle.net/1721.1/139865
dc.description.abstractDesign reuse is a common practice in the space industry — stemming from a desire by engineers and managers to realize cost and schedule benefits while buying down risk with proven designs. Legacy design reuse, specifically, is characterized by its opportunistic nature compared to more intentional platform-based reuse. However, legacy reuse decisions made during preliminary phases of an architecting effort are often overly optimistic regarding potential benefits. This can lead to reuse scenarios that either do not fully realize expected benefits, or result in detrimental impacts or even mission failure. This work presents a remedy in the form of the Legacy Design Reuse in MBSE (LDRM) methodology. It is a systematic approach for conducting technical and programmatic analyses for informing legacy reuse decisions in the early design phases of a mission. LDRM incorporates design reuse best practices and process improvements derived from a survey of industry practitioners. The resulting procedure is implemented in a Model-based Systems Engineering (MBSE) environment in order to leverage the integrated, authoritative, and curated data landscape of this new paradigm. Key outputs of LDRM are: a) assessment of reuse feasibility of a candidate design, b) enumeration of the required rework/adaptation effort, and c) estimate of the reuse scenario’s cost or schedule impacts versus a comparable from-scratch effort - using the COSYSMO 2.0 parametric cost modeling tool. A sample design problem demonstrates application of LDRM to evaluate reuse of the robotic arm design of the Curiosity rover on Luna, a hypothetical lunar rover. The Luna design case is carried into a two-phase virtual Lego design/build/reuse validation experiment. Decision-making performance of study participants with access to LDRM outputs is improved by close to 30% over a control group. LDRM is then applied to two industry case studies. The first, reuse of the bus subsystems across the AeroCube 10 and DAILI CubeSat missions, demonstrates nominal procedures and outcomes for 3 of 4 subsystems explored; model incompatibilities in the attitude control system led to recommendations to the sponsor for improvements to MBSE model practices and curation. The second case study, exploring congressionally-mandated reuse in NASA’s SLS vehicle, finds reuse limitations in the Core Stage engine section borrowed from the Space Shuttle program. LDRM predicts a 43% increase in systems engineering effort due to extensive interface rework of engine section components. These real-world findings suggest that decision support tools, like LDRM, can improve legacy reuse outcomes in the next generation of space systems.
dc.publisherMassachusetts Institute of Technology
dc.rightsIn Copyright - Educational Use Permitted
dc.rightsCopyright MIT
dc.rights.urihttp://rightsstatements.org/page/InC-EDU/1.0/
dc.titleA Model-based Methodology for Strategic Reuse of Legacy Designs in Space Mission Architecting
dc.typeThesis
dc.description.degreePh.D.
dc.contributor.departmentMassachusetts Institute of Technology. Department of Aeronautics and Astronautics
dc.identifier.orcid0000-0002-7028-581X
mit.thesis.degreeDoctoral
thesis.degree.nameDoctor of Philosophy


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